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dc.contributor.authorDean, JAen_US
dc.contributor.authorWelsh, LCen_US
dc.contributor.authorWong, KHen_US
dc.contributor.authorAleksic, Aen_US
dc.contributor.authorDunne, Een_US
dc.contributor.authorIslam, MRen_US
dc.contributor.authorPatel, Aen_US
dc.contributor.authorPatel, Pen_US
dc.contributor.authorPetkar, Ien_US
dc.contributor.authorPhillips, Ien_US
dc.contributor.authorSham, Jen_US
dc.contributor.authorSchick, Uen_US
dc.contributor.authorNewbold, KLen_US
dc.contributor.authorBhide, SAen_US
dc.contributor.authorHarrington, KJen_US
dc.contributor.authorNutting, CMen_US
dc.contributor.authorGulliford, SLen_US
dc.coverage.spatialEnglanden_US
dc.date.accessioned2017-03-01T12:13:39Z
dc.date.issued2017-04en_US
dc.identifierhttps://www.ncbi.nlm.nih.gov/pubmed/28057404en_US
dc.identifierS0936-6555(16)30415-0en_US
dc.identifier.citationClin Oncol (R Coll Radiol), 2017, 29 (4), pp. 263 - 273en_US
dc.identifier.urihttps://repository.icr.ac.uk/handle/internal/438
dc.identifier.eissn1433-2981en_US
dc.identifier.doi10.1016/j.clon.2016.12.001en_US
dc.description.abstractAIMS: A normal tissue complication probability (NTCP) model of severe acute mucositis would be highly useful to guide clinical decision making and inform radiotherapy planning. We aimed to improve upon our previous model by using a novel oral mucosal surface organ at risk (OAR) in place of an oral cavity OAR. MATERIALS AND METHODS: Predictive models of severe acute mucositis were generated using radiotherapy dose to the oral cavity OAR or mucosal surface OAR and clinical data. Penalised logistic regression and random forest classification (RFC) models were generated for both OARs and compared. Internal validation was carried out with 100-iteration stratified shuffle split cross-validation, using multiple metrics to assess different aspects of model performance. Associations between treatment covariates and severe mucositis were explored using RFC feature importance. RESULTS: Penalised logistic regression and RFC models using the oral cavity OAR performed at least as well as the models using mucosal surface OAR. Associations between dose metrics and severe mucositis were similar between the mucosal surface and oral cavity models. The volumes of oral cavity or mucosal surface receiving intermediate and high doses were most strongly associated with severe mucositis. CONCLUSIONS: The simpler oral cavity OAR should be preferred over the mucosal surface OAR for NTCP modelling of severe mucositis. We recommend minimising the volume of mucosa receiving intermediate and high doses, where possible.en_US
dc.format.extent263 - 273en_US
dc.languageengen_US
dc.language.isoengen_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_US
dc.subjectHead and neck radiotherapyen_US
dc.subjectNTCP modellingen_US
dc.subjectOAR delineationen_US
dc.subjectmachine learningen_US
dc.subjectmucositisen_US
dc.subjectoral mucosaen_US
dc.subjectAdolescenten_US
dc.subjectAdulten_US
dc.subjectAgeden_US
dc.subjectAged, 80 and overen_US
dc.subjectHead and Neck Neoplasmsen_US
dc.subjectHumansen_US
dc.subjectLogistic Modelsen_US
dc.subjectMiddle Ageden_US
dc.subjectModels, Biologicalen_US
dc.subjectMouth Mucosaen_US
dc.subjectMucositisen_US
dc.subjectProbabilityen_US
dc.subjectRadiotherapyen_US
dc.subjectRadiotherapy Dosageen_US
dc.subjectReproducibility of Resultsen_US
dc.subjectYoung Adulten_US
dc.titleNormal Tissue Complication Probability (NTCP) Modelling of Severe Acute Mucositis using a Novel Oral Mucosal Surface Organ at Risk.en_US
dc.typeJournal Article
dcterms.dateAccepted2016-11-01en_US
rioxxterms.versionofrecord10.1016/j.clon.2016.12.001en_US
rioxxterms.licenseref.startdate2017-04en_US
rioxxterms.typeJournal Article/Reviewen_US
dc.relation.isPartOfClin Oncol (R Coll Radiol)en_US
pubs.issue4en_US
pubs.notesNo embargoen_US
pubs.organisational-group/ICR
pubs.organisational-group/ICR/Primary Group
pubs.organisational-group/ICR/Primary Group/ICR Divisions
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Cancer Biology
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Cancer Biology/Targeted Therapy
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging/Clinical Academic Radiotherapy (Horwich)
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging/Radiotherapy Physics Modelling
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging/Targeted Therapy
pubs.organisational-group/ICR/Primary Group/Royal Marsden Clinical Units
pubs.publication-statusPublisheden_US
pubs.volume29en_US
pubs.embargo.termsNo embargoen_US
icr.researchteamClinical Academic Radiotherapy (Horwich)en_US
icr.researchteamRadiotherapy Physics Modellingen_US
icr.researchteamTargeted Therapyen_US
dc.contributor.icrauthorHarrington, Kevinen_US
dc.contributor.icrauthorGulliford, Sarahen_US
dc.contributor.icrauthorDean, Jamieen_US
dc.contributor.icrauthorMarsden,en_US


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